About

Ganna Pugach is a robotics researcher whose work lies at the intersection of tactile sensing, neural control, and human-robot interaction. Her research focuses on endowing robots with a sense of touch, enabling them to perceive and physically interact with humans and their environment in a more natural and safe manner. Pugach’s major contributions include developing a neural controller that uses artificial skin input to adapt a robot arm’s compliance in multiple directions, a breakthrough for safe physical human-robot interaction (cited 19 times). She has also pioneered brain-inspired coding of robot body schema, using Gain-Field neuron models to integrate visuo-motor and tactile events—a key step toward aligning sensorimotor reference frames in robots (cited 13 times). Additionally, Pugach designed a low-cost tactile sensor system based on Electrical Impedance Tomography (EIT) using conductive fabric, making artificial skin more accessible for research and application (cited 8 times). Her work bridges neuroscience and robotics, offering elegant solutions for robots to “feel” and adapt. With a growing citation footprint, Pugach is a rising voice in embodied AI, demonstrating how tactile intelligence can transform robots from rigid machines into perceptive, collaborative partners.

Research Focus

Key Achievements

3
H-Index
3
Papers
40
Total Citations
13
Avg Citations/Paper
🏆 Most Cited Paper
Touch-based admittance control of a robotic arm using neural learning of an artificial skin
19 citations · 2016
📈 Most Prolific Year: 2016 (1 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: Centre National de la Recherche Scientifique, École Nationale Supérieure de l'Électronique et de ses Applications, Donetsk National Technical University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago